Prediction of Human Induced Pluripotent Stem Cell Formation Based on Deep Learning Analyses Using Time-lapse Brightfield Microscopy Images-Reference-Cited by-同舟云学术

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Prediction of Human Induced Pluripotent Stem Cell Formation Based on Deep Learning Analyses Using Time-lapse Brightfield Microscopy Images

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Chu Slo-Li¹,Sudo Kazuhiro²,Abe Kuniya²,Yokota Hideo³,Nakamura Yukio²,Liou Guan-Ting⁴,Tsai Ming-Dar¹

Affiliation:

1. Chung-Yuan Christian University,Department of Information and Computer Engineering,Chung-Li,Taiwan,32023

2. BioResource Research Center,Tsukuba,Ibaraki,Japan,305-0074

3. Center for Advanced Photonics,Wako,,Saitama,Japan,351-0198

4. Chung-Yuan Christian University.,Master Program in Depnartment of Information and Computer Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871815.pdf?arnumber=9871815

Reference9 articles.

1. A System for Automated, Noninvasive, Morphology-Based Evaluation of Induced Pluripotent Stem Cell Cultures

2. Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells

3. Very deep convolutional networks for large-scale image recognition;simonyan;ArXiv,2015

4. Visualization of morphological categories of colonies for monitoring of effect on induced pluripotent stem cell culture status

5. High Resolution U-Net for Quantitatively Analyzing Early Spatial Patterning of Human Induced Pluripotent Stem Cells on Micropatterns

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